Introduction to GRASS GIS
Basic notions, interfaces and temporal framework
GRASS GIS general stuff
- GRASS GIS (Geographic Resources Analysis Support System), a FOSS suite used for geospatial data management and analysis, image processing, graphics and maps, spatial modeling, and visualization.
- Originally developed by the U.S. Army Construction Engineering Research Laboratories for land management and environmental planning (1982-1995).
- More history: https://grass.osgeo.org/about/history/
- Free and open source, you can use, modify, improve, share
- Strong user community, commercial support
- Large amount of tools: 500+ core modules, 300+ addons
- GUI and CLI interfaces
- Python API and libraries - new
grass.jupyterlibrary can be tried online - Connection with R, QGIS, WPS, etc.
- Different data types supported: raster (including satellite imagery), 3D raster or voxel, vector and space-time datasets
Open GRASS for the first time
As of version 8.0, GRASS has modified its startup to make it more user friendly:
From the Data catalog tab you can manage several actions and if you do not yet have imported data into the GRASS database, the software creates the directory structure or database automatically.
Database
-
GRASS database (directory with projects): When running GRASS GIS for the first time, a folder named “grassdata” is automatically created. Depending on the operating system, it can be found in
$HOME(*nix) orMy Documents(MS Windows). - Location (a project): A location is defined by its coordinate reference system (CRS). The location that is automatically created is in WGS84 (EPSG:4326). If you have data in another CRS, you should ideally create a new location.
- Mapset (a subproject): Each location can have many mapsets to manage different aspects or sub-regions of a project. When creating a new location, GRASS GIS automatically creates a special mapset called PERMANENT where the central data of the project (e.g., base maps, road network, dem, etc.) can be stored.
More info: https://grass.osgeo.org/grass-stable/manuals/grass_database.html.
Computational region
Another fundamental concept of GRASS GIS (and very useful when working with raster data) is that of the computational region. It refers to the boundary configuration of the analysis area and spatial resolution (raster). The computational region can be defined and modified with the command g.region to the extent of a vector map, a raster or manually to some area of interest. The output raster maps will have an extent and spatial resolution equal to the computational region, while vector maps are always processed at their original extent.
For more details, see the wiki on Computational Region.
Modules and extensions
GRASS has more than 500 modules for the most varied tasks:
| Prefix | Function class | Type of command | Example |
|---|---|---|---|
| g.* | general | general data management | g.rename: renames map |
| d.* | display | graphical output | d.rast: display raster map |
| r.* | raster | raster processing | r.mapcalc: map algebra |
| v.* | vector | vector processing | v.clean: topological cleaning |
| i.* | imagery | imagery processing | i.pca: Principal Components Analysis on imagery group |
| r3.* | voxel | 3D raster processing | r3.stats: voxel statistics |
| db.* | database | database management | db.select: select value(s) from table |
| ps.* | postscript | PostScript map creation | ps.map: PostScript map creation |
| t.* | temporal | space-time datasets | t.rast.aggregate: raster time series aggregation |
Extensions or add-ons can be installed from the central GitHub repository or from other users’ GitHub (or similar repositories) using the command g.extension. For example:
Graphical User Interface (GUI)
Command line
GRASS + Python
Python package grass.script
The grass.script or GRASS GIS Python Scripting Library provides functions for calling GRASS modules within Python scripts. The most commonly used functions include:
-
run_command: used when the output of the modules is a raster or vector, no text type output is expected -
read_command: used when the output of the modules is of text type -
parse_command: used with modules whose output can be converted tokey=valuepairs -
write_command: used with modules that expect text input, either in the form of a file or from stdin
It also provides several wrapper functions for frequently used modules, for example:
- To get info from a raster, script.raster.raster_info() is used:
gs.raster_info('dsm') - To get info of a vector, script.vector.vector_info() is used:
gs.vector_info('roads') - To list the raster in a location, script.core.list_grouped() is used:
gs.list_grouped(type=['raster']) - To obtain the computational region, script.core.region() is used:
gs.region()
More info: https://grass.osgeo.org/grass-stable/manuals/libpython/script_intro.html
Python package grass.jupyter
The grass.jupyter library improves the integration of GRASS and Jupyter, and provides different classes to facilitate GRASS maps visualization:
-
init: starts a GRASS session and sets up all necessary environment variables -
Map: 2D rendering -
Map3D: 3D rendering -
InteractiveMap: interactive visualization with folium -
TimeSeriesMap: visualization for spatio-temporal data
More info: https://grass.osgeo.org/grass-stable/manuals/libpython/grass.jupyter.html
GRASS + R through rgrass package
We can use R within a GRASS GIS session or use GRASS GIS within an R session
Demo session overview
Habitat suitability mapping for the Asian tiger mosquito in Northern Italy based on variables derived from daily LST data
-
GRASS
- Import species records
- Create random background points
- Create different environmental layers from daily LST data
-
R
- Read data from GRASS into R
- Model species distribution
- Model evaluation
- Visualization of results
Jarnevich et al. 2015. doi:10.1016/j.ecoinf.2015.06.007
Data for the session
- Records of Aedes albopictus (Asian tiger mosquito) in Northern Italy downloaded from GBIF
- Daily MODIS LST reconstructed by mundialis based on Metz et al. 2017
- 1 km spatial resolution
- Converted to Celsius degrees
Get sample location, mosquito records and code
- Create a folder named
grassdata - Download and unzip eu_laea location with LST mapset and unzip within your
grassdatafolder - Download the asian tiger mosquito occurrences as
.gpkgfile
The grassdata_ogh folder’s tree should look like this:
grassdata_ogh/
└── eu_laea
├── italy_LST_daily
└── PERMANENTMASK
- Masks are set with r.mask or creating a raster map called
MASK. - Masks are virtual masks, they are only actually applied when reading raster maps
- All cells that are NULL in the MASK map will be ignored (also all areas outside the computational region).
- Vector maps can be also used as masks
a- Elevation raster and lakes vector maps. b- Only the raster data inside the masked area are used for further analysis. c- Inverse mask.
MASK examples
# use vector as mask
r.mask vector=lakes
# use vector as mask, set inverse mask
r.mask -i vector=lakes
# mask categories of a raster map
r.mask raster=landclass96 maskcats="5 thru 7"
# create a raster named MASK
r.mapcalc expression="MASK = if(elevation < 100, 1, null())"
# remove mask
r.mask -rMasks are only actually applied when reading a GRASS raster map, i.e., when used as input.
GRASS GIS HELP!!!
- g.manual: in the main GUI under Help or just pressing F1
-
--helpor--hflag after the module name in the terminal - GRASS website: rich learn section with links to videos, tutorials, courses, books, etc.
- GRASS wiki: examples, explanations on particular modules or tasks, tutorials, applications, etc.
- grass-user mailing list: subscribe and post or check the archives
- Link to source code and history in each module manual page, eg., t.rast.algebra
